Currently, camera systems are used to capture audio and video of multiple participants at a location. In particular, videoconferencing sessions are used to conduct meetings or otherwise allow people to communicate from different locations. Often times videoconferencing sessions include multiple people who are illuminated differently at the same location in the videoconferencing session. This creates problems when setting exposure levels for capturing a video feed, e.g. in video conferencing sessions. Specifically, current cameras typically use an average brightness across participants in a session to set an exposure level for capturing a video feed in the session. This averaging technique can lead to exposure levels that are incorrect or otherwise leave an active participant over exposed or under exposed in a video feed. Specifically, large differences in illumination levels of different participants in a session can lead to an averaged exposure level that is incorrect for a current active participant. There therefore exist needs for correctly setting an exposure of a video feed of a session for an active participant, e.g. not under or over exposing the active participant, when participants are illuminated differently at a location in the session.
Further, current camera systems use face detections to control automatic exposure of captured video feeds of sessions. Current face detection algorithms identify face detections by applying machine learning or specific feature extraction methods to images or videos captured at a location in a session. This can lead to false detections of faces in a video session. For example, current face detection algorithms can identify a reflection of a participant as an actual face detection. In turn, as face detections are used to control automatic exposure of a captured video feed, falsely identified face detections can distort or otherwise cause setting of incorrect exposures for the capture video feed in a session. For example, an identified face detection of a reflection can include low illumination levels at the reflection that are used to set a reduced exposure level for a captured video feed. This reduced exposure level can be lower than an ideal exposure level for the captured video feed leading to incorrect exposure of an active participant in the video feed. There therefore exist needs for eliminating an impact of false face detections on setting exposure levels of video feeds, e.g. in a videoconferencing session.